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Metabolic profiling analysis of the degradation of phenol and 4-chlorophenol by Pseudomonas sp. cbp1-3
Biochemical Engineering Journal 90 (2014) 316–323
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Metabolic profiling analysis of the degradation of phenol and 4-chlorophenol by Pseudomonas sp. cbp1-3 Yingjie Liu a,1 , Jiao Liu a,1 , Chen Li a , Jianping Wen a,b,c , Rui Ban a,b , Xiaoqiang Jia a,b,c,∗ a b c
Department of Biological Engineering, School of Chemical Engineering and Technology, Tianjin 300072, PR China Key Laboratory of Systems Bioengineering (Tianjin University), Ministry of Education, Tianjin 300072, PR China Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, PR China
a r t i c l e
i n f o
Article history: Received 25 February 2014 Received in revised form 29 April 2014 Accepted 30 June 2014 Available online 8 July 2014 Keywords: Metabolic profiling analysis Biodegradation Chromatography Microbial growth Waste treatment Pseudomonas sp.
a b s t r a c t To investigate the enhancement of phenol on the biodegradation of 4-chlorophenol (4-cp), metabolic profiling approach was performed for the first time to analyze metabolite changes of Pseudomonas sp. cbp1-3 using single substrate (succinate, phenol, and 4-cp) and dual substrate (mixtures of phenol and 4-cp). Phosphoric acid, ␥-aminobutyric acid, 4-cp, 4-chlorocatechol, and catechol were shown to change significantly. Results indicated that phenols, especially 4-cp, depressed cell growth by inhibiting its primary metabolic pathway. In addition, the addition of phenol into the 4-cp-containing medium had a global influence on cells including the accumulation of amino acids, amines, saturated fatty acids, and monoacylglycerols as well as the concentration changes of metabolite participating in phenols biodegradation, thus enhancing the degradation of 4-cp. This study provided novel insights into the biodegradation of mixed phenolic compounds and the method could be used to investigate the biodegradation of complicated multi-pollutants. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Phenols are pollutants of environmental concerns due to their wide use in agricultural and industrial processes [1]. Biodegradation of phenols has been studied extensively, for instance, screening microorganism for phenols degradation, studying degradation pathways or biodegradation kinetics, and optimizing cultural conditions [2,3]. However, unlike single phenols used under the lab, phenols mostly occur as mixtures in nature, increasing the difficulty in their degradation. Some microorganisms are able to degrade these compounds simultaneously [4]; but often the degradation of one compound is severely inhibited by another, which results in the sequential utilization of phenolic compounds [5]. Additionally the degradation of compounds with higher toxicity (for example 4cp) is enhanced by the less toxic ones (for example phenol), which functions as growth substrates [6]. It seems that interactions among phenols play an important role in their biodegradation.
∗ Corresponding author at: Department of Biological Engineering, School of Chemical Engineering and Technology, Tianjin 300072, PR China. Tel.: +86 22 27890492; fax: +86 22 27403389. E-mail address: [email protected] (X. Jia). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.bej.2014.06.026 1369-703X/© 2014 Elsevier B.V. All rights reserved.
Despite the increasing interest in the biodegradation of phenol mixtures, little is known about the interaction mechanism among them. Previous studies mostly focused on the characterization of the degradation process and degradation kinetics. In the post genomic era, systems biology especially metabolomics provided new tools for studying the biodegradation of phenols and systematically examining the metabolism changes at the intracellular metabolites level. Metabolomics is the study of the interactions of living organisms with their natural environments at the metabolic level [7]. It reflects the metabolic changes of microorganism in response to the environmental stimuli, which intuitively reveals the reactive mechanism to the surroundings. Metabolomics has been successfully applied to study changes of intracellular metabolites when bacteria suffer from heat shock, oxidative stress, osmotic stress, metal stress and solvent stress [7,8]. Cells may respond to single stimulus by cellular changes in glycolysis pathway, tricarboxylic acid (TCA) cycle, amino acid metabolism, fatty acid metabolism and nucleic acid metabolism, in order to remediate the stress. Similarly, metabolomics could be used to study the responsive mechanism of phenols. Strain Pseudomonas sp. cbp1-3 isolated in our lab, displayed ability to degrade phenols [2]. In addition, phenol has been shown to enhance the biodegradation of 4-cp. In the study, we used Pseudomonas sp. cbp1-3 as an example to study the degradation
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of pollutants using metabolomics methods. Gas chromatography coupled to mass spectrometry (GC–MS) was used to assess intracellular metabolite spectra for further evaluating the enhancement effect.
2. Materials and methods 2.1. Microorganisms and cultivation conditions Pseudomonas sp. cbp1-3 stocked in our laboratory was isolated from activated sludge of a coking plant in Tianjin [2]. Strain cbp1-3 was grown in minimal medium supplemented with the following compounds as the sole carbon source (succinate 250 mg l−1 , phenol 200 mg l−1 , 4-cp 100 mg l−1 , mixtures of 200 mg l−1 phenol and 100 mg l−1 4-cp, respectively). The initial pH of the medium was adjusted to 7.2 with 2 mol l−1 NaOH. All cultivations were carried out at 30 ◦ C and 200 rpm.
2.2. Analysis of residual succinate and phenols in the medium The concentration of succinate and phenols were determined by the methods described by Unell et al. with some modifications [5]. The supernatant was prepared by centrifugation at 6000 × g for 10 min and then filtered through syringe filters with a pore size of 0.22 m. The residual substrate concentrations in the supernatant were measured using high performance liquid chromatography (HPLC, 1200, Agilent, USA) equipped with a Zorbax Eclipse SB-C18 column (250 mm × 4.6 mm, 5 m, Agilent, USA) and a UV-detector (G1313B, Agilent, USA). For detecting succinate, 5 mM H2 SO4 was used as the mobile phase at a flow rate of 0.8 ml min−1 . The column temperature was set at 65 ◦ C and UV absorption at 210 nm. For detecting phenol and 4-cp, the mobile phase of methanol/water (57/43, v/v) at a flow rate of 1.0 ml min−1 was used. The column temperature was set at 30 ◦ C and the wavelength of UV-detector was set at 280 nm. The retention time for phenol, 4-cp and succinate was 3.87 min, 6.75 min and 17.75 min, respectively.
2.3. Determination of intracellular metabolites Cells were sampled when the degradation of phenols started. The sampling points were chosen at 5 h of cells in the succinate medium, 6 h in the phenol medium, 22 h in the 4-cp medium, and 12 h in the mixed medium of phenol and 4-cp, respectively. These sampling time points were showed by pink arrows (Fig. 1). Sample quenching, extraction and derivatization were carried out according to methods described previously [9].
2.4. GC–MS data processing and statistical analysis The GC–MS data was processed by the Mass Spectral Deconvolution and Identification System, Version 3.2 for peak recognition, identification, and deconvolution. The peaks with a peak width of 2.0 s and a signal/noise values above 10 were identified as metabolite peaks. The peak areas of all metabolites were normalized with the internal standards and biomass concentrations in the same chromatograms. Metabolites identification was performed by comparing the mass spectra with NIST mass spectral library [8]. After centering and scaling, the datasets derived from metabolite profiling were analyzed by principal component analysis (PCA) as well as hierarchical cluster analysis (HCA) using Matlab. Five biological replicates were used to perform multivariate analysis for each sample.
Fig. 1. Degradation of succinate, phenol, 4-cp and phenolic compounds by Pseudomonas sp. cbp1-3. (a) Degradation of single-substrate. (b) Degradation of phenol and 4-chlorophenol mixtures. Arrows (1), (2), (3) and (4) show the sampling times of succinate, phenol, 4-cp and mixtures of phenol and 4-cp, respectively. (For interpretation of the references to color in text near the reference citation, the reader is referred to the web version of this article.)
3. Results and discussion 3.1. Degradation performance of Pseudomonas sp. cbp1-3 Minimal medium containing succinate, phenol, 4-cp and mixtures of phenol and 4-cp as carbon sources were used in the research. Glucose is a widely used growth substrate under laboratory condition, but it is not a good carbon source for Pseudomonas due to its inefficient degradation via the Entner–Doudoroff pathway [10]. Succinate is preferentially metabolized by Pseudomonas and thus used in this study as a positive control [11]. In the single-substrate degradation, succinate was the fastest one degraded by cells, 3.2 g l−1 of succinate was completely degraded after 6 h with a lag phase of 4 h; 200 mg l−1 phenol was degraded after 7 h with a lag phase of 5 h; and 100 mg l−1 of 4cp was degraded after 40 h with a lag phase of 10 h. Due to the interaction of phenol and 4-cp, in the dual-substrate degradation, the degradation time of phenol extended to 18 h, while for 4-cp it was shorten to 22 h (Fig. 1). It could be seen that phenol significantly enhanced the degradation of 4-cp with the degradation time of 100 mg l−1 4-cp shortened from 40 h to 22 h when phenol was added to the 4-cp medium. In this study, we investigated the enhancement effect of phenol to the biodegradation of 4-cp using the metabolic profiling approach. 3.2. Multivariate data analysis The metabolites of Pseudomonas sp. cbp1-3 from 20 samples of four different media (five replicated from each medium) were analyzed by GC–MS. A total of 160 intracellular metabolites were detected with 93 of them identified, including amino acids, organic acids, amines, phosphorylated compounds, monoacylglycerols (MAGs) and fatty acids. Cluster analysis (PCA and HCA) was applied for analyzing the metabolites identified. It allowed the distinction among samples as well as the determination of important
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Fig. 2. PCA score plot a and loading plot b of intracellular metabolites. The first three principal components accounted for 52.83%, 25.28% and 8.13%, respectively, of the total variance.
metabolites that influenced cluster formation in these samples. Results indicated that Pseudomonas responded globally to different substrates especially the phenol and 4-cp mixtures. 3.2.1. PCA PCA was used as an unsupervised tool to visualize the data by reducing the dimensionality of the multivariate data. In the PCA score plot, each data point representing a linear combination of all the metabolites. In the PCA loading plot, each data point represented a certain metabolite, and the data point further from the origin has a stronger influence on the differences. The score plot of PCA was used for judging the similarities as well as differences among samples, while the PCA loading plot was used to identify the corresponding biomarkers responsible for the discrimination [12]. With the help of PCA, we found that substrate composition had an important influence on the metabolic profile of the strain cbp1-3. The first three principal components made up 86.24% of the total variance, while the first and second principal component accounted for 52.83% and 25.28%, respectively. In the score plot of PCA, samples from various carbon sources were clearly divided into four groups (Fig. 2a), indicating that the metabolism of Pseudomonas exhibited different characteristics when different substrates were used. It can be seen in the PCA loading plot that phosphoric acid, ␥-aminobutyric acid (GABA), 4-cp, 4-chlorocatechol, and catechol significantly contributed to the cluster formation (Fig. 2b). Other metabolites such as lactate, amino acids, amines, MAGs as well as fatty acids also affected the cluster formation. 3.2.2. HCA In order to further illustrate the enhancement of phenol on the degradation 4-cp by Pseudomonas, the metabolite concentrations were also analyzed by HCA. According to the hierarchical clustered heat map of the 93 metabolites identified (Fig. 3), metabolites displayed different levels among samples and metabolites with similar variation trend clustered together. Both the intermediates of central carbon metabolism and amino acids displayed a decreasing trend in the single-substrate system of succinate, phenol and 4-cp. While there was an increasing trend in amino acids, amines, fatty acids, MAGs, and sugars among phenols samples. These metabolites accumulated at the highest level in mixtures of phenol and 4-cp sample. These different metabolic changes among samples could provide important information for phenols degradation especially the enhancement of phenol to 4-cp degradation.
3.3. The inhibition effect on the cell growth It has been reported that phenols inhibited cell growth mainly by damaging cell membrane and uncoupling oxidative phosphorylation [14,15]. When comparing metabolic changes in the single-substrate degradation of succinate to the changes in the phenol and 4-cp, it was found that cells responded globally to phenols, which were closely related to the primary metabolism including central carbon metabolism, amino acid metabolism and phosphoric acid metabolism. 3.3.1. Central carbon metabolism Our results showed that central carbon metabolism was more vigorous and the levels of intermediates including oxalate, malate, citrate, glycerol-3-phosphate, and glycerate-3-phosphate were higher when using succinate as the substrate compared with those in cells growing on phenols (Fig. 3 and Table 1). Their levels in the phenol sample were decreased by about 2.5-, 2.0-, 8.0-, 10.0and 2.5-fold, respectively, compared with those using succinate as substrate. And the levels of these metabolites were even lower when 4-cp was used as the substrate as shown in Table 1. Compared to phenols, succinate was a better carbon source which cells could utilize faster. These results indicated that phenols severely inhibited central carbon metabolism and then inhibited cell growth and reproduction due to the highly toxicity. 3.3.2. Amino acid metabolism In the single-substrate degradation, the levels of amino acids including glycine, proline, aspartate, threonine, tyrosine, and glutamine reduced gradually in the order of succinate, phenol, and 4-cp sample (Fig. 3 and Table 1). The levels of glycine and glutamine decreased by about 2- and 1.5-fold in the phenol sample and 2.5- and 5-fold in the 4-cp sample, respectively, compared with those in the succinate sample. This may be due to the inhibition of central carbon metabolism as described in Section 3.3.1, some of which could be used as precursors for amino acids synthesis. The down-regulation enzymes required for amino acids degradation was also found in benzoate-grown cells according to Cao and Loh [16]. As a 1-C donor, glycine participates in the biosynthesis of many important metabolites such as protein and purines [17]. Glutamine is considered as the major nitrogen source which plays a main role in nitrogen metabolism. It is also a precursor for the biosynthesis of other amino acids and nucleotides [8]. In addition,
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the decreasing level of glutamine was likely related to nitrogen depletion. Taken together, our results suggested that phenols especially 4-cp inhibited the amino acid metabolism, which affected cell growth eventually. 3.3.3. Phosphoric acid metabolism In our study, the level of phosphoric acid in the phenol and the 4-cp sample increased by 1.31-fold and 3.75-fold, respectively, compared with that in the succinate sample (Table 1). Phosphoric acid is an important metabolite participating in phosphorylation of ADP to ATP and compounds associating with the TCA cycle as well as the regulation of signal transduction in response to the environmental stress [8]. The low level of phosphoric acid indicated that central carbon metabolism and energy metabolism were very active in the succinate sample with a large amount of phosphoric acid participating in it. While the high level of phosphoric acid in the phenols sample might imply that central carbon metabolism and energy metabolism were hindered in the degradation of phenols. Uncoupled oxidative phosphorylation caused by phenols could also contribute to the accumulation of phosphoric acid. From the analysis above, we revealed new inhibition effect caused by phenols at the metabolic level. Compared to succinate, the control substrate used in our research, phenol and 4-cp could reduce the primary metabolism which eventually inhibited cell growth. Our research also indicated that 4-cp had a more seriously influence on cell growth. It was consistent with the previously report that the substitution of hydrogen with a chloride electron on the aromatic ring of 4-cp diminished enzymatic transformation and deactivated electrophilic substitution, which affected the introduction of a second hydroxyl group onto the aromatic ring [18]. Compared to phenol, 4-cp was more toxic and harder to degrade. 3.4. The promotion effect of phenol on the degradation of 4-cp According to previous research, phenol could relieve the inhibition of cell growth by 4-cp through the accumulation of cell mass. During cell growth, the gradients across the membrane can be restored; the membrane composition and fluidity can be modified to repair the permeability of the membrane [14]. In addition, phenol can also induce and initiate the synthesis of some substrates (enzymes et al.) required for 4-cp transformation [6]. So in the degradation of 4-cp, phenol is often used as a co-substrate to enhance its degradation [19]. This study further analyzed the enhancement effect at the metabolic level.
Fig. 3. Hierarchical clustering heat map of all 93 found metabolites among different samples (s01–s05: phenol, s06–s10: 4-cp, s11–s15: mixtures of phenol and 4-cp, s16–s20: succinate).
3.4.1. Amino acids In sharp contrast to the low level of amino acids in singlesubstrate sample as described in Section 3.3.2, the amino acids level was enhanced substantially in the phenolic mixtures sample (Fig. 3 and Table 2), even reaching that in the succinate sample. The high level of amino acids could be a result of increased protein degradation, which eliminates abnormal proteins formed under stress condition – phenolic stress in our study [20]. Additionally, amino acids are the precursor of many compounds such as proteins, nucleic acids, and nitrogen containing substances. While the protein degradation could also be seen as an important way to increase the availability of amino acids required for the synthesis of necessary compounds used for survival under stress conditions [21]. Another important finding was the accumulation of high level of non-proteinogenic amino acid – GABA in phenolic mixtures sample (Fig. 3 and Table 2). GABA was derived from the amination and decarboxylation of 2-ketoglutarate which normally oxidatively decarboxylated to succinate in the TCA cycle [22]. The activation of GABA shunt might be caused by an enhanced NADH/NAD+ ratio [23]. Panagiotou et al. found that GABA shunt played a key role in
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Table 1 The comparison of intracellular metabolite concentration from cultures in single-substrate system. Classification
Metabolite
Single-substrate system Succinatea
Phenol
4-cp
Carbohydrate metabolism
Oxalate Malate Citrate Glycerol-3-phosphate Glycerate-3-phosphate
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.09 0.03 0.25 0.09 0.07
0.40 0.57 0.13 0.22 0.41
± ± ± ± ±
0.09 0.01 0.03 0.02 0.07
0.26 0.59 0.06 0.10 0.32
± ± ± ± ±
0.04 0.02 0.01 0.02 0.02
Amino acid metabolism
Glycine Proline Threonine Tyrosine Aspartate Glutamine
1.00 1.00 1.00 1.00 1.00 1.00
± ± ± ± ± ±
0.07 0.01 0.01 0.01 0.01 0.08
0.58 0.91 0.90 0.97 0.99 0.71
± ± ± ± ± ±
0.02 0.01 0.01 0.00 0.01 0.01
0.44 0.85 0.85 0.96 0.96 0.20
± ± ± ± ± ±
0.06 0.01 0.01 0.00 0.01 0.01
Phosphoric metabolism
Phosphoric acid
1.00 ± 0.06
a
1.31 ± 0.03
3.75 ± 0.32
In order to facilitate data comparison, the amount of metabolites in succinate sample was set as 1.00.
maintaining redox equilibrium while the elevated level of GABA shunt may be an indication of redox imbalance under stress conditions [24]. In addition, the increasing amount of lactate in phenolic mixtures sample may be also due to the high level of NADH in cells. As described by Wang and Loh [6] that NADH required for 4-cp transformation could be efficiently regenerated during the oxidation of phenol. Apart from its role in many primary metabolisms required for cell growth and regeneration, NADH also acted as a cofactor of phenolic dioxygenase and monooxygenase in the degradation of phenols. We came to a conclusion that higher contents of GABA and lactate could be seen as the indicator of the enhanced NADH level which could promote the degradation and utilization of phenols.
3.4.2. Amines Large amount of amines such as ethylamine, propylamine, hydroxylamine, 1,4-butanediamine, and 1,2-ethandiamine were detected in the phenolic mixtures sample. Their levels in the phenolic mixtures sample were increased by 1.85-, 1.92-, 2.68-, 1.99- and 1.22-fold, respectively, compared with those in the phenol sample as shown in Table 2. Amines especially polyamines can promote the synthesis of proteins and nuclear acids which play a crucial role in cell growth. Additionally, the accumulation of polyamines can protect cells from environmental pressure [25]. This finding indicated that the strain cbp1-3 tolerated unfavorable environments by protecting metabolites in phenolic mixtures sample in some way.
Table 2 The comparison of intracellular metabolite concentration from cultures in phenols substrate. Classification
Metabolite
Phenolic substrates Phenola
4-cp
4-cp and phenol
Amino acids
Glycine Proline Threonine Tyrosine GABA
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.03 0.01 0.01 0.00 0.03
0.77 0.94 0.95 0.99 0.20
± ± ± ± ±
0.14 0.02 0.01 0.00 0.03
1.23 1.05 1.06 1.01 2.26
± ± ± ± ±
0.03 0.02 0.01 0.00 0.03
Amines
Ethylamine Propylamine Hydroxylamine 1,4-Butanediamine 1,2-Ethandiamine
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.15 0.10 0.29 0.17 0.04
1.38 0.83 1.81 1.25 0.95
± ± ± ± ±
0.20 0.09 0.07 0.06 0.04
1.85 1.92 2.68 1.99 1.22
± ± ± ± ±
0.15 0.53 0.14 0.13 0.08
Fatty acids
Docosanoate Tetradecanoic acid Hexadecanoate Heptadecanoic acid Stearate Eicosanoic acid Tetracosanoic acid (9Z)-Octadecenoic acid Linoleate Vaccenic acid
1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
± ± ± ± ± ± ± ± ± ±
0.12 0.13 0.08 0.17 0.23 0.11 0.04 0.16 0.12 0.08
1.21 1.05 1.31 2.14 1.09 0.84 0.85 0.72 0.98 0.23
± ± ± ± ± ± ± ± ± ±
0.06 0.11 0.07 0.18 0.18 0.23 0.14 0.11 0.01 0.01
3.06 1.18 1.45 3.82 1.64 1.07 1.14 0.38 0.76 2.30
± ± ± ± ± ± ± ± ± ±
0.49 0.11 0.26 0.31 0.20 0.16 0.11 0.03 0.11 0.08
MAGs
2-Monopalmitin 1-Monohexadecanoylglycerol 1-Monolinoleoylglycerol 1-Octadecanoylglycerol
1.00 1.00 1.00 1.00
± ± ± ±
0.12 0.19 0.22 0.18
1.08 1.39 1.27 1.44
± ± ± ±
0.10 0.12 0.26 0.10
1.63 1.91 1.95 1.97
± ± ± ±
0.27 0.16 0.57 0.16
Sugars
Talose Fructose Mannose Sedoheptulose Maltose
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.24 0.15 0.22 0.16 0.10
1.24 1.78 0.99 1.07 1.25
± ± ± ± ±
0.14 0.28 0.14 0.10 0.10
1.60 4.25 2.82 1.84 3.11
± ± ± ± ±
0.19 0.46 0.31 0.07 0.60
a
In order to facilitate data comparison, the amount of metabolites in phenol sample was set as 1.00.
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Fig. 4. Degradation pathways of phenol and 4-cp and the relative abundance of the intermediates. (a) The relative abundance of 4-chlirocatechol. (b) The relative abundance of benzenetriol. (c) The relative abundance of catechol. (d) The relative abundance of hydroquinone. (e) Metabolite pathways in degrading of phenol and 4-cp.
3.4.3. Fatty acids Phenols strongly affected membrane permeability and fluidity with the accumulation of fatty acids. An increase in saturated fatty acid (SFA) such as dococanoate, tetradecanoic acid, hexadecanoate, heptadecanoic acid, stearate, eicosanoic acid, and tetracosanoic acid as well as a decrease in unsaturated fatty acid (UFA) such as linoleate and (9z)-octadecenoic acid were found in the phenolic mixtures sample in this study (Fig. 3 and Table 2). Heipieper et al. [26] observed the same phenomenon that the increase in the degree of saturation fatty acids correlated with the increased tolerance of Pseudomonas putida P8 toward phenolic compounds. Altering the UFA to SFA ratio and increasing degree of saturation of fatty acid could be seen as a major adaptive mechanism through which cell membrane gained more resistance to the fluidizing action when exposing to toxic phenolic compounds. As a result, Pseudomonas had enhanced resistance to phenols. In addition, large amounts of vaccenic acid accumulated in the phenolic mixture. The existence of vaccenic acid indicated the presence of the anaerobic fatty acid biosynthesis pathway and the absence of desaturase system in the aerobic fatty acid synthesis pathway [27]. The activation of GABA and lactate shunt discussed in Section 3.4.1 could also been caused by anaerobic conditions [28]. Collectively, these findings indicated that oxygen supplying was insufficient or oxygen transfer was blocked in the phenolic mixture sample. When researching the process of phenol degradation, Kapley et al. [29] came to the conclusion that oxygen played an important role on it. Using 2-hydroxymuconate semialdehyde (HMS), an intermediate in the phenol degradation pathway, as a
reference to assess the degradation of phenol, they found that the level of HMS changed from the maximum accumulation of 3.92 M to below 0.4 M when DO was enhanced from 2 to 3 ppm. Following these, the DO level could be optimized to enhance the phenols degradation when using the mixtures of phenol and 4-cp as substrates. 3.4.4. MAGs It was noteworthy that large amounts of MAGs such as 1-octadecanoylglycerol, 21-monohexadecanoylglycerol, monopalmitin, and 1-monolinoleolglycerol were detected in the phenolic samples especially in the mixture of phenol and 4-cp sample (Fig. 3 and Table 2). Their levels in the phenolic mixture sample were increased by 1.63-, 1.91-, 1.95- and 1.97-fold, respectively, compared with those in the phenol sample as shown in Table 2. Apart from their role in cellular energy storage and signaling transduction, MAGs also functioned as transmembrane Cl− /NO3 − anion transporters [30]. In our opinion, phenol enhanced the degradation of the 4-cp and during this process a lot of Cl− was released to the cell. And it required high level of MAGs to transport the enhanced level of Cl− to maintain the transmembrane ion balance which in turn promoted the degradation of 4-cp. MAGs could acted as indicators of the chlorocatechols degradation. 3.4.5. Sugars Extra energy was required for cells to survive and adapt to phenol stress, because a number of energetically expensive adaptation mechanisms could be triggered [31]. Thus it demands more energy
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for the biodegradation of aromatic compounds; and the inhibition of metabolism as discussed in Section 3.3 could be seen as an energy conservation strategy. The energy stored was used preferentially for degrading phenols, the sole carbon and energy source, to maintain the basic survival. A similar phenomenon was found that a large amount of soluble sugars such as talose, fructose, mannose, sedoheptulose and maltose were accumulated in the phenolic mixture sample. Their levels in the phenolic mixture sample were increased by 1.60-, 4.25-, 2.82-, 1.84- and 3.11-fold, respectively, compared with those in the phenol sample as shown in Table 2. Sugars are well-known carbon sources and play essential roles in carbon and energy metabolism as well as in polymer biosynthesis [32]. The accumulation of sugars could be seen as a way to conserve energy for further utilization. 3.5. The interaction between phenol and 4-cp As discussed above that phenol caused a global influence on cell to enhance the degradation of 4-cp. Besides, there was interaction between them in their degradation because phenol and 4-cp were structurally analogous. Compare to the 4-cp sample, the level of hydroquinone and benzenetriol increased 50% while catechol and 4-chlorocatechol decreased 40% in the phenolic mixture sample (Fig. 4). These results implied that the strain cbp1-3 might prefer the hydroquinone–benzenetriol degradation pathway when using the phenol and 4-cp mixture as the substrate. The effective toxicity of phenolic compounds to cells was highly dependent on their degradation pathways [33]. It is likely using the same degradation pathway, cells could use the same enzyme systems and eliminate the competition of different pathways to enhance the degradation efficiency [4]. Additionally catechol could inhibit the transformation of 4-cp and the meta-cleavage products of chlorocatechols were thought to be lethal or unable to support cell growth [34]. These findings could provide useful information for further investigating the phenols degradation. 4. Conclusions Metabolic profiling analysis was used for the first time to investigate the degradation of phenol and 4-cp by Pseudomonas sp. cbp1-3. Samples from different substrates (succinate, phenol, 4cp, and the mixture of phenol and 4-cp) were clearly separated by performing PCA on the detected intracellular metabolites in the score plot. Furthermore, it was found that phenols inhibited cell growth by reducing its primary metabolism while phenols enhanced the degradation of 4-cp in their mixed medium through accumulating amino acids, polyamines, and saturated fatty acids which were thought as the common tolerance mechanisms for cells. Besides, the accumulation of Cl− transduction carrier-MAGs and concentration changes of metabolites participating in phenols biodegradation aided in a deeper understanding of the degradation of phenols. The observed variations of intracellular metabolites led to a better understanding of the co-degradation of phenol and 4-cp and gave insights into the enhancement effect of phenol on 4chlorophenol at the intracellular molecular level. According to our results, primary metabolism, DO level, and the balance of reducing power should be considered for further enhancing the degradation of phenolic compounds. Additionally, the regulation of key enzymes associated in relative degradation pathways can be also modulated to enhance the degradation. By comparing metabolite changes of Pseudomonas sp. cbp1-3 in single substrate (phenol and 4-cp) and dual substrate (mixtures of phenol and 4-cp), results revealed that metabolomics is an effective tool to investigate the enhancement of phenol by 4-cp in their co-degradation. Although metabolomics studies have provided valuable information, it needs to be used in conjunction with
other systems biology approaches to enable integrated physiological analysis in order to provide a comprehensive interpretation of phenols degradation. With a good experimental design, an effective analysis method, and an integration with other approaches, metabolomics can be used as a powerful tool to enhance phenols degradation and other pollutants. Acknowledgements The authors wish to acknowledge the financial support provided by the National Key Basic Research Program of China (No. 2014CB745100), the National Natural Science Foundation of China (No. 20906070), Tianjin Research Program of Application Foundation and Advanced Technology (No. 14JCQNJC06700), and the Seed Foundation of Tianjin University and the Program of Introducing Talents of Discipline to Universities (No. B06006). We would like to say many thanks to Dr. Kang Wu, an assistant professor of the Department of Chemical Engineering, University of New Hampshire, for providing many valuable suggestions as well as particular attention to language use on this paper. References [1] J. Jensen, Chlorophenols in the terrestrial environment, Rev. Environ. Contam. Toxicol. 146 (1996) 25–51. [2] J. Liu, X.Q. Jia, J.P. Wen, Z.X. Zhou, Substrate interactions and kinetics study of phenolic compounds biodegradation by Pseudomonas sp. cbp 1-3, Biochem. Eng. J. 67 (2012) 156–166. [3] B. Basak, B. Bhunia, S. Dutta, A. Dey, Enhanced biodegradation of 4-chlorophenol by Candida tropicalis PHB5 via optimization of physicochemical parameters using Taguchi orthogonal array approach, Int. Biodeter. Biodegr. 78 (2013) 17–23. [4] Z. Liu, C. Yang, C.L. Qiao, Biodegradation of p-nitrophenol and 4-chlorophenol by Stenotrophomonas sp., FEMS Microbiol. Lett. 277 (2007) 150–156. [5] M. Unell, K. Nordin, C. Jernberg, J. Stenstrom, J.K. Jansson, Degradation of mixtures of phenolic compounds by Arthrobacter chlorophenolicus A6, Biodegradation 19 (2008) 495–505. [6] S.J. Wang, K.C. Loh, New cell growth pattern on mixed substrates and substrate utilization in cometabolic transformation of 4-chlorophenol, Water Res. 34 (2000) 3786–3794. [7] M.R. Viant, U. Sommer, Mass spectrometry based environmental metabolomics: a primer and review, Metabolomics 9 (2013) 144–158. [8] M.Z. Ding, J.S. Cheng, W.H. Xiao, B. Qiao, Y.J. Yuan, Comparative metabolomic analysis on industrial continuous and batch ethanol fermentation processes by GC–TOF-MS, Metabolomics 5 (2009) 229–238. [9] M.L. Xia, D. Huang, S.S. Li, J.P. Wen, X.Q. Jia, Y.L. Chen, Enhanced FK506 production in Streptomyces tsukubaensis by rational feeding strategies based on comparative metabolic profiling analysis, Biotechnol. Bioeng. 110 (2013) 2717–2730. [10] A. Goldbourt, L.A. Day, A.E. McDermott, Assignment of congested NMR spectra: carbonyl backbone enrichment via the Entner–Doudoroff pathway, J. Magn. Reson. 189 (2007) 157–165. [11] M.J. van der Werf, K.M. Overkamp, B. Muilwijk, M.M. Koek, B.J. van der Werffvan, R.H. Jellema, L. Coulier, T. Hankemeier, Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources, Mol. Biosyst. 4 (2008) 315–327. [12] M.Z. Ding, H.C. Tian, J.S. Cheng, Y.J. Yuan, Inoculum size-dependent interactive regulation of metabolism and stress response of Saccharomyces cerevisiae revealed by comparative metabolomics, J. Biotechnol. 144 (2009) 279–286. [14] H.J. Heipeiper, H. Keweloh, H.J. Rehm, Influence of phenols on growth and membrane permeability of free and immobilized Escherichia coli, Appl. Environ. Microb. 57 (1991) 1213–1217. [15] B.I. Escher, M. Snozzi, R.P. Schwarzenbach, Uptake, speciation, and uncoupling activity of substituted phenols in energy transducing membranes, Environ. Sci. Technol. 30 (1996) 3071–3079. [16] B. Cao, K.C. Loh, Catabolic pathways and cellular responses of Pseudomonas putida P8 during growth on benzoate with a proteomics approach, Biotechnol. Bioeng. 101 (2008) 1297–1312. [17] R. Abrams, E. Hammarsten, D. Shemin, Glycine as a precursor of purines in yeast, J. Biol. Chem. 173 (1948) 429–430. [18] A. Farrell, B. Quilty, Substrate-dependent autoaggregation of Pseudomonas putida CP1 during the degradation of mono-chlorophenols and phenol, J. Ind. Microbiol. Biotechnol. 28 (2002) 316–324. [19] P.B. Saez, B.E. Rittmann, Biodegradation kinetics of a mixture containing a primary substrate (phenol) and an inhibitory co-metabolite (4-chlorophenol), Biodegradation 4 (1993) 3–21. [20] S. Jozefczuk, S. Klie, G. Catchpole, J. Szymanski, A. Cuadros-Inostroza, D. Steinhauser, J. Selbig, L. Willmitzer, Metabolomic and transcriptomic stress response of Escherichia coli, Mol. Syst. Biol. 6 (2010) 364.
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Metabolic profiling analysis of the degradation of phenol and 4-chlorophenol by Pseudomonas sp. cbp1-3 Yingjie Liu a,1 , Jiao Liu a,1 , Chen Li a , Jianping Wen a,b,c , Rui Ban a,b , Xiaoqiang Jia a,b,c,∗ a b c
Department of Biological Engineering, School of Chemical Engineering and Technology, Tianjin 300072, PR China Key Laboratory of Systems Bioengineering (Tianjin University), Ministry of Education, Tianjin 300072, PR China Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, PR China
a r t i c l e
i n f o
Article history: Received 25 February 2014 Received in revised form 29 April 2014 Accepted 30 June 2014 Available online 8 July 2014 Keywords: Metabolic profiling analysis Biodegradation Chromatography Microbial growth Waste treatment Pseudomonas sp.
a b s t r a c t To investigate the enhancement of phenol on the biodegradation of 4-chlorophenol (4-cp), metabolic profiling approach was performed for the first time to analyze metabolite changes of Pseudomonas sp. cbp1-3 using single substrate (succinate, phenol, and 4-cp) and dual substrate (mixtures of phenol and 4-cp). Phosphoric acid, ␥-aminobutyric acid, 4-cp, 4-chlorocatechol, and catechol were shown to change significantly. Results indicated that phenols, especially 4-cp, depressed cell growth by inhibiting its primary metabolic pathway. In addition, the addition of phenol into the 4-cp-containing medium had a global influence on cells including the accumulation of amino acids, amines, saturated fatty acids, and monoacylglycerols as well as the concentration changes of metabolite participating in phenols biodegradation, thus enhancing the degradation of 4-cp. This study provided novel insights into the biodegradation of mixed phenolic compounds and the method could be used to investigate the biodegradation of complicated multi-pollutants. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Phenols are pollutants of environmental concerns due to their wide use in agricultural and industrial processes [1]. Biodegradation of phenols has been studied extensively, for instance, screening microorganism for phenols degradation, studying degradation pathways or biodegradation kinetics, and optimizing cultural conditions [2,3]. However, unlike single phenols used under the lab, phenols mostly occur as mixtures in nature, increasing the difficulty in their degradation. Some microorganisms are able to degrade these compounds simultaneously [4]; but often the degradation of one compound is severely inhibited by another, which results in the sequential utilization of phenolic compounds [5]. Additionally the degradation of compounds with higher toxicity (for example 4cp) is enhanced by the less toxic ones (for example phenol), which functions as growth substrates [6]. It seems that interactions among phenols play an important role in their biodegradation.
∗ Corresponding author at: Department of Biological Engineering, School of Chemical Engineering and Technology, Tianjin 300072, PR China. Tel.: +86 22 27890492; fax: +86 22 27403389. E-mail address: [email protected] (X. Jia). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.bej.2014.06.026 1369-703X/© 2014 Elsevier B.V. All rights reserved.
Despite the increasing interest in the biodegradation of phenol mixtures, little is known about the interaction mechanism among them. Previous studies mostly focused on the characterization of the degradation process and degradation kinetics. In the post genomic era, systems biology especially metabolomics provided new tools for studying the biodegradation of phenols and systematically examining the metabolism changes at the intracellular metabolites level. Metabolomics is the study of the interactions of living organisms with their natural environments at the metabolic level [7]. It reflects the metabolic changes of microorganism in response to the environmental stimuli, which intuitively reveals the reactive mechanism to the surroundings. Metabolomics has been successfully applied to study changes of intracellular metabolites when bacteria suffer from heat shock, oxidative stress, osmotic stress, metal stress and solvent stress [7,8]. Cells may respond to single stimulus by cellular changes in glycolysis pathway, tricarboxylic acid (TCA) cycle, amino acid metabolism, fatty acid metabolism and nucleic acid metabolism, in order to remediate the stress. Similarly, metabolomics could be used to study the responsive mechanism of phenols. Strain Pseudomonas sp. cbp1-3 isolated in our lab, displayed ability to degrade phenols [2]. In addition, phenol has been shown to enhance the biodegradation of 4-cp. In the study, we used Pseudomonas sp. cbp1-3 as an example to study the degradation
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of pollutants using metabolomics methods. Gas chromatography coupled to mass spectrometry (GC–MS) was used to assess intracellular metabolite spectra for further evaluating the enhancement effect.
2. Materials and methods 2.1. Microorganisms and cultivation conditions Pseudomonas sp. cbp1-3 stocked in our laboratory was isolated from activated sludge of a coking plant in Tianjin [2]. Strain cbp1-3 was grown in minimal medium supplemented with the following compounds as the sole carbon source (succinate 250 mg l−1 , phenol 200 mg l−1 , 4-cp 100 mg l−1 , mixtures of 200 mg l−1 phenol and 100 mg l−1 4-cp, respectively). The initial pH of the medium was adjusted to 7.2 with 2 mol l−1 NaOH. All cultivations were carried out at 30 ◦ C and 200 rpm.
2.2. Analysis of residual succinate and phenols in the medium The concentration of succinate and phenols were determined by the methods described by Unell et al. with some modifications [5]. The supernatant was prepared by centrifugation at 6000 × g for 10 min and then filtered through syringe filters with a pore size of 0.22 m. The residual substrate concentrations in the supernatant were measured using high performance liquid chromatography (HPLC, 1200, Agilent, USA) equipped with a Zorbax Eclipse SB-C18 column (250 mm × 4.6 mm, 5 m, Agilent, USA) and a UV-detector (G1313B, Agilent, USA). For detecting succinate, 5 mM H2 SO4 was used as the mobile phase at a flow rate of 0.8 ml min−1 . The column temperature was set at 65 ◦ C and UV absorption at 210 nm. For detecting phenol and 4-cp, the mobile phase of methanol/water (57/43, v/v) at a flow rate of 1.0 ml min−1 was used. The column temperature was set at 30 ◦ C and the wavelength of UV-detector was set at 280 nm. The retention time for phenol, 4-cp and succinate was 3.87 min, 6.75 min and 17.75 min, respectively.
2.3. Determination of intracellular metabolites Cells were sampled when the degradation of phenols started. The sampling points were chosen at 5 h of cells in the succinate medium, 6 h in the phenol medium, 22 h in the 4-cp medium, and 12 h in the mixed medium of phenol and 4-cp, respectively. These sampling time points were showed by pink arrows (Fig. 1). Sample quenching, extraction and derivatization were carried out according to methods described previously [9].
2.4. GC–MS data processing and statistical analysis The GC–MS data was processed by the Mass Spectral Deconvolution and Identification System, Version 3.2 for peak recognition, identification, and deconvolution. The peaks with a peak width of 2.0 s and a signal/noise values above 10 were identified as metabolite peaks. The peak areas of all metabolites were normalized with the internal standards and biomass concentrations in the same chromatograms. Metabolites identification was performed by comparing the mass spectra with NIST mass spectral library [8]. After centering and scaling, the datasets derived from metabolite profiling were analyzed by principal component analysis (PCA) as well as hierarchical cluster analysis (HCA) using Matlab. Five biological replicates were used to perform multivariate analysis for each sample.
Fig. 1. Degradation of succinate, phenol, 4-cp and phenolic compounds by Pseudomonas sp. cbp1-3. (a) Degradation of single-substrate. (b) Degradation of phenol and 4-chlorophenol mixtures. Arrows (1), (2), (3) and (4) show the sampling times of succinate, phenol, 4-cp and mixtures of phenol and 4-cp, respectively. (For interpretation of the references to color in text near the reference citation, the reader is referred to the web version of this article.)
3. Results and discussion 3.1. Degradation performance of Pseudomonas sp. cbp1-3 Minimal medium containing succinate, phenol, 4-cp and mixtures of phenol and 4-cp as carbon sources were used in the research. Glucose is a widely used growth substrate under laboratory condition, but it is not a good carbon source for Pseudomonas due to its inefficient degradation via the Entner–Doudoroff pathway [10]. Succinate is preferentially metabolized by Pseudomonas and thus used in this study as a positive control [11]. In the single-substrate degradation, succinate was the fastest one degraded by cells, 3.2 g l−1 of succinate was completely degraded after 6 h with a lag phase of 4 h; 200 mg l−1 phenol was degraded after 7 h with a lag phase of 5 h; and 100 mg l−1 of 4cp was degraded after 40 h with a lag phase of 10 h. Due to the interaction of phenol and 4-cp, in the dual-substrate degradation, the degradation time of phenol extended to 18 h, while for 4-cp it was shorten to 22 h (Fig. 1). It could be seen that phenol significantly enhanced the degradation of 4-cp with the degradation time of 100 mg l−1 4-cp shortened from 40 h to 22 h when phenol was added to the 4-cp medium. In this study, we investigated the enhancement effect of phenol to the biodegradation of 4-cp using the metabolic profiling approach. 3.2. Multivariate data analysis The metabolites of Pseudomonas sp. cbp1-3 from 20 samples of four different media (five replicated from each medium) were analyzed by GC–MS. A total of 160 intracellular metabolites were detected with 93 of them identified, including amino acids, organic acids, amines, phosphorylated compounds, monoacylglycerols (MAGs) and fatty acids. Cluster analysis (PCA and HCA) was applied for analyzing the metabolites identified. It allowed the distinction among samples as well as the determination of important
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Fig. 2. PCA score plot a and loading plot b of intracellular metabolites. The first three principal components accounted for 52.83%, 25.28% and 8.13%, respectively, of the total variance.
metabolites that influenced cluster formation in these samples. Results indicated that Pseudomonas responded globally to different substrates especially the phenol and 4-cp mixtures. 3.2.1. PCA PCA was used as an unsupervised tool to visualize the data by reducing the dimensionality of the multivariate data. In the PCA score plot, each data point representing a linear combination of all the metabolites. In the PCA loading plot, each data point represented a certain metabolite, and the data point further from the origin has a stronger influence on the differences. The score plot of PCA was used for judging the similarities as well as differences among samples, while the PCA loading plot was used to identify the corresponding biomarkers responsible for the discrimination [12]. With the help of PCA, we found that substrate composition had an important influence on the metabolic profile of the strain cbp1-3. The first three principal components made up 86.24% of the total variance, while the first and second principal component accounted for 52.83% and 25.28%, respectively. In the score plot of PCA, samples from various carbon sources were clearly divided into four groups (Fig. 2a), indicating that the metabolism of Pseudomonas exhibited different characteristics when different substrates were used. It can be seen in the PCA loading plot that phosphoric acid, ␥-aminobutyric acid (GABA), 4-cp, 4-chlorocatechol, and catechol significantly contributed to the cluster formation (Fig. 2b). Other metabolites such as lactate, amino acids, amines, MAGs as well as fatty acids also affected the cluster formation. 3.2.2. HCA In order to further illustrate the enhancement of phenol on the degradation 4-cp by Pseudomonas, the metabolite concentrations were also analyzed by HCA. According to the hierarchical clustered heat map of the 93 metabolites identified (Fig. 3), metabolites displayed different levels among samples and metabolites with similar variation trend clustered together. Both the intermediates of central carbon metabolism and amino acids displayed a decreasing trend in the single-substrate system of succinate, phenol and 4-cp. While there was an increasing trend in amino acids, amines, fatty acids, MAGs, and sugars among phenols samples. These metabolites accumulated at the highest level in mixtures of phenol and 4-cp sample. These different metabolic changes among samples could provide important information for phenols degradation especially the enhancement of phenol to 4-cp degradation.
3.3. The inhibition effect on the cell growth It has been reported that phenols inhibited cell growth mainly by damaging cell membrane and uncoupling oxidative phosphorylation [14,15]. When comparing metabolic changes in the single-substrate degradation of succinate to the changes in the phenol and 4-cp, it was found that cells responded globally to phenols, which were closely related to the primary metabolism including central carbon metabolism, amino acid metabolism and phosphoric acid metabolism. 3.3.1. Central carbon metabolism Our results showed that central carbon metabolism was more vigorous and the levels of intermediates including oxalate, malate, citrate, glycerol-3-phosphate, and glycerate-3-phosphate were higher when using succinate as the substrate compared with those in cells growing on phenols (Fig. 3 and Table 1). Their levels in the phenol sample were decreased by about 2.5-, 2.0-, 8.0-, 10.0and 2.5-fold, respectively, compared with those using succinate as substrate. And the levels of these metabolites were even lower when 4-cp was used as the substrate as shown in Table 1. Compared to phenols, succinate was a better carbon source which cells could utilize faster. These results indicated that phenols severely inhibited central carbon metabolism and then inhibited cell growth and reproduction due to the highly toxicity. 3.3.2. Amino acid metabolism In the single-substrate degradation, the levels of amino acids including glycine, proline, aspartate, threonine, tyrosine, and glutamine reduced gradually in the order of succinate, phenol, and 4-cp sample (Fig. 3 and Table 1). The levels of glycine and glutamine decreased by about 2- and 1.5-fold in the phenol sample and 2.5- and 5-fold in the 4-cp sample, respectively, compared with those in the succinate sample. This may be due to the inhibition of central carbon metabolism as described in Section 3.3.1, some of which could be used as precursors for amino acids synthesis. The down-regulation enzymes required for amino acids degradation was also found in benzoate-grown cells according to Cao and Loh [16]. As a 1-C donor, glycine participates in the biosynthesis of many important metabolites such as protein and purines [17]. Glutamine is considered as the major nitrogen source which plays a main role in nitrogen metabolism. It is also a precursor for the biosynthesis of other amino acids and nucleotides [8]. In addition,
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the decreasing level of glutamine was likely related to nitrogen depletion. Taken together, our results suggested that phenols especially 4-cp inhibited the amino acid metabolism, which affected cell growth eventually. 3.3.3. Phosphoric acid metabolism In our study, the level of phosphoric acid in the phenol and the 4-cp sample increased by 1.31-fold and 3.75-fold, respectively, compared with that in the succinate sample (Table 1). Phosphoric acid is an important metabolite participating in phosphorylation of ADP to ATP and compounds associating with the TCA cycle as well as the regulation of signal transduction in response to the environmental stress [8]. The low level of phosphoric acid indicated that central carbon metabolism and energy metabolism were very active in the succinate sample with a large amount of phosphoric acid participating in it. While the high level of phosphoric acid in the phenols sample might imply that central carbon metabolism and energy metabolism were hindered in the degradation of phenols. Uncoupled oxidative phosphorylation caused by phenols could also contribute to the accumulation of phosphoric acid. From the analysis above, we revealed new inhibition effect caused by phenols at the metabolic level. Compared to succinate, the control substrate used in our research, phenol and 4-cp could reduce the primary metabolism which eventually inhibited cell growth. Our research also indicated that 4-cp had a more seriously influence on cell growth. It was consistent with the previously report that the substitution of hydrogen with a chloride electron on the aromatic ring of 4-cp diminished enzymatic transformation and deactivated electrophilic substitution, which affected the introduction of a second hydroxyl group onto the aromatic ring [18]. Compared to phenol, 4-cp was more toxic and harder to degrade. 3.4. The promotion effect of phenol on the degradation of 4-cp According to previous research, phenol could relieve the inhibition of cell growth by 4-cp through the accumulation of cell mass. During cell growth, the gradients across the membrane can be restored; the membrane composition and fluidity can be modified to repair the permeability of the membrane [14]. In addition, phenol can also induce and initiate the synthesis of some substrates (enzymes et al.) required for 4-cp transformation [6]. So in the degradation of 4-cp, phenol is often used as a co-substrate to enhance its degradation [19]. This study further analyzed the enhancement effect at the metabolic level.
Fig. 3. Hierarchical clustering heat map of all 93 found metabolites among different samples (s01–s05: phenol, s06–s10: 4-cp, s11–s15: mixtures of phenol and 4-cp, s16–s20: succinate).
3.4.1. Amino acids In sharp contrast to the low level of amino acids in singlesubstrate sample as described in Section 3.3.2, the amino acids level was enhanced substantially in the phenolic mixtures sample (Fig. 3 and Table 2), even reaching that in the succinate sample. The high level of amino acids could be a result of increased protein degradation, which eliminates abnormal proteins formed under stress condition – phenolic stress in our study [20]. Additionally, amino acids are the precursor of many compounds such as proteins, nucleic acids, and nitrogen containing substances. While the protein degradation could also be seen as an important way to increase the availability of amino acids required for the synthesis of necessary compounds used for survival under stress conditions [21]. Another important finding was the accumulation of high level of non-proteinogenic amino acid – GABA in phenolic mixtures sample (Fig. 3 and Table 2). GABA was derived from the amination and decarboxylation of 2-ketoglutarate which normally oxidatively decarboxylated to succinate in the TCA cycle [22]. The activation of GABA shunt might be caused by an enhanced NADH/NAD+ ratio [23]. Panagiotou et al. found that GABA shunt played a key role in
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Table 1 The comparison of intracellular metabolite concentration from cultures in single-substrate system. Classification
Metabolite
Single-substrate system Succinatea
Phenol
4-cp
Carbohydrate metabolism
Oxalate Malate Citrate Glycerol-3-phosphate Glycerate-3-phosphate
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.09 0.03 0.25 0.09 0.07
0.40 0.57 0.13 0.22 0.41
± ± ± ± ±
0.09 0.01 0.03 0.02 0.07
0.26 0.59 0.06 0.10 0.32
± ± ± ± ±
0.04 0.02 0.01 0.02 0.02
Amino acid metabolism
Glycine Proline Threonine Tyrosine Aspartate Glutamine
1.00 1.00 1.00 1.00 1.00 1.00
± ± ± ± ± ±
0.07 0.01 0.01 0.01 0.01 0.08
0.58 0.91 0.90 0.97 0.99 0.71
± ± ± ± ± ±
0.02 0.01 0.01 0.00 0.01 0.01
0.44 0.85 0.85 0.96 0.96 0.20
± ± ± ± ± ±
0.06 0.01 0.01 0.00 0.01 0.01
Phosphoric metabolism
Phosphoric acid
1.00 ± 0.06
a
1.31 ± 0.03
3.75 ± 0.32
In order to facilitate data comparison, the amount of metabolites in succinate sample was set as 1.00.
maintaining redox equilibrium while the elevated level of GABA shunt may be an indication of redox imbalance under stress conditions [24]. In addition, the increasing amount of lactate in phenolic mixtures sample may be also due to the high level of NADH in cells. As described by Wang and Loh [6] that NADH required for 4-cp transformation could be efficiently regenerated during the oxidation of phenol. Apart from its role in many primary metabolisms required for cell growth and regeneration, NADH also acted as a cofactor of phenolic dioxygenase and monooxygenase in the degradation of phenols. We came to a conclusion that higher contents of GABA and lactate could be seen as the indicator of the enhanced NADH level which could promote the degradation and utilization of phenols.
3.4.2. Amines Large amount of amines such as ethylamine, propylamine, hydroxylamine, 1,4-butanediamine, and 1,2-ethandiamine were detected in the phenolic mixtures sample. Their levels in the phenolic mixtures sample were increased by 1.85-, 1.92-, 2.68-, 1.99- and 1.22-fold, respectively, compared with those in the phenol sample as shown in Table 2. Amines especially polyamines can promote the synthesis of proteins and nuclear acids which play a crucial role in cell growth. Additionally, the accumulation of polyamines can protect cells from environmental pressure [25]. This finding indicated that the strain cbp1-3 tolerated unfavorable environments by protecting metabolites in phenolic mixtures sample in some way.
Table 2 The comparison of intracellular metabolite concentration from cultures in phenols substrate. Classification
Metabolite
Phenolic substrates Phenola
4-cp
4-cp and phenol
Amino acids
Glycine Proline Threonine Tyrosine GABA
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.03 0.01 0.01 0.00 0.03
0.77 0.94 0.95 0.99 0.20
± ± ± ± ±
0.14 0.02 0.01 0.00 0.03
1.23 1.05 1.06 1.01 2.26
± ± ± ± ±
0.03 0.02 0.01 0.00 0.03
Amines
Ethylamine Propylamine Hydroxylamine 1,4-Butanediamine 1,2-Ethandiamine
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.15 0.10 0.29 0.17 0.04
1.38 0.83 1.81 1.25 0.95
± ± ± ± ±
0.20 0.09 0.07 0.06 0.04
1.85 1.92 2.68 1.99 1.22
± ± ± ± ±
0.15 0.53 0.14 0.13 0.08
Fatty acids
Docosanoate Tetradecanoic acid Hexadecanoate Heptadecanoic acid Stearate Eicosanoic acid Tetracosanoic acid (9Z)-Octadecenoic acid Linoleate Vaccenic acid
1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
± ± ± ± ± ± ± ± ± ±
0.12 0.13 0.08 0.17 0.23 0.11 0.04 0.16 0.12 0.08
1.21 1.05 1.31 2.14 1.09 0.84 0.85 0.72 0.98 0.23
± ± ± ± ± ± ± ± ± ±
0.06 0.11 0.07 0.18 0.18 0.23 0.14 0.11 0.01 0.01
3.06 1.18 1.45 3.82 1.64 1.07 1.14 0.38 0.76 2.30
± ± ± ± ± ± ± ± ± ±
0.49 0.11 0.26 0.31 0.20 0.16 0.11 0.03 0.11 0.08
MAGs
2-Monopalmitin 1-Monohexadecanoylglycerol 1-Monolinoleoylglycerol 1-Octadecanoylglycerol
1.00 1.00 1.00 1.00
± ± ± ±
0.12 0.19 0.22 0.18
1.08 1.39 1.27 1.44
± ± ± ±
0.10 0.12 0.26 0.10
1.63 1.91 1.95 1.97
± ± ± ±
0.27 0.16 0.57 0.16
Sugars
Talose Fructose Mannose Sedoheptulose Maltose
1.00 1.00 1.00 1.00 1.00
± ± ± ± ±
0.24 0.15 0.22 0.16 0.10
1.24 1.78 0.99 1.07 1.25
± ± ± ± ±
0.14 0.28 0.14 0.10 0.10
1.60 4.25 2.82 1.84 3.11
± ± ± ± ±
0.19 0.46 0.31 0.07 0.60
a
In order to facilitate data comparison, the amount of metabolites in phenol sample was set as 1.00.
Y. Liu et al. / Biochemical Engineering Journal 90 (2014) 316–323
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Fig. 4. Degradation pathways of phenol and 4-cp and the relative abundance of the intermediates. (a) The relative abundance of 4-chlirocatechol. (b) The relative abundance of benzenetriol. (c) The relative abundance of catechol. (d) The relative abundance of hydroquinone. (e) Metabolite pathways in degrading of phenol and 4-cp.
3.4.3. Fatty acids Phenols strongly affected membrane permeability and fluidity with the accumulation of fatty acids. An increase in saturated fatty acid (SFA) such as dococanoate, tetradecanoic acid, hexadecanoate, heptadecanoic acid, stearate, eicosanoic acid, and tetracosanoic acid as well as a decrease in unsaturated fatty acid (UFA) such as linoleate and (9z)-octadecenoic acid were found in the phenolic mixtures sample in this study (Fig. 3 and Table 2). Heipieper et al. [26] observed the same phenomenon that the increase in the degree of saturation fatty acids correlated with the increased tolerance of Pseudomonas putida P8 toward phenolic compounds. Altering the UFA to SFA ratio and increasing degree of saturation of fatty acid could be seen as a major adaptive mechanism through which cell membrane gained more resistance to the fluidizing action when exposing to toxic phenolic compounds. As a result, Pseudomonas had enhanced resistance to phenols. In addition, large amounts of vaccenic acid accumulated in the phenolic mixture. The existence of vaccenic acid indicated the presence of the anaerobic fatty acid biosynthesis pathway and the absence of desaturase system in the aerobic fatty acid synthesis pathway [27]. The activation of GABA and lactate shunt discussed in Section 3.4.1 could also been caused by anaerobic conditions [28]. Collectively, these findings indicated that oxygen supplying was insufficient or oxygen transfer was blocked in the phenolic mixture sample. When researching the process of phenol degradation, Kapley et al. [29] came to the conclusion that oxygen played an important role on it. Using 2-hydroxymuconate semialdehyde (HMS), an intermediate in the phenol degradation pathway, as a
reference to assess the degradation of phenol, they found that the level of HMS changed from the maximum accumulation of 3.92 M to below 0.4 M when DO was enhanced from 2 to 3 ppm. Following these, the DO level could be optimized to enhance the phenols degradation when using the mixtures of phenol and 4-cp as substrates. 3.4.4. MAGs It was noteworthy that large amounts of MAGs such as 1-octadecanoylglycerol, 21-monohexadecanoylglycerol, monopalmitin, and 1-monolinoleolglycerol were detected in the phenolic samples especially in the mixture of phenol and 4-cp sample (Fig. 3 and Table 2). Their levels in the phenolic mixture sample were increased by 1.63-, 1.91-, 1.95- and 1.97-fold, respectively, compared with those in the phenol sample as shown in Table 2. Apart from their role in cellular energy storage and signaling transduction, MAGs also functioned as transmembrane Cl− /NO3 − anion transporters [30]. In our opinion, phenol enhanced the degradation of the 4-cp and during this process a lot of Cl− was released to the cell. And it required high level of MAGs to transport the enhanced level of Cl− to maintain the transmembrane ion balance which in turn promoted the degradation of 4-cp. MAGs could acted as indicators of the chlorocatechols degradation. 3.4.5. Sugars Extra energy was required for cells to survive and adapt to phenol stress, because a number of energetically expensive adaptation mechanisms could be triggered [31]. Thus it demands more energy
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for the biodegradation of aromatic compounds; and the inhibition of metabolism as discussed in Section 3.3 could be seen as an energy conservation strategy. The energy stored was used preferentially for degrading phenols, the sole carbon and energy source, to maintain the basic survival. A similar phenomenon was found that a large amount of soluble sugars such as talose, fructose, mannose, sedoheptulose and maltose were accumulated in the phenolic mixture sample. Their levels in the phenolic mixture sample were increased by 1.60-, 4.25-, 2.82-, 1.84- and 3.11-fold, respectively, compared with those in the phenol sample as shown in Table 2. Sugars are well-known carbon sources and play essential roles in carbon and energy metabolism as well as in polymer biosynthesis [32]. The accumulation of sugars could be seen as a way to conserve energy for further utilization. 3.5. The interaction between phenol and 4-cp As discussed above that phenol caused a global influence on cell to enhance the degradation of 4-cp. Besides, there was interaction between them in their degradation because phenol and 4-cp were structurally analogous. Compare to the 4-cp sample, the level of hydroquinone and benzenetriol increased 50% while catechol and 4-chlorocatechol decreased 40% in the phenolic mixture sample (Fig. 4). These results implied that the strain cbp1-3 might prefer the hydroquinone–benzenetriol degradation pathway when using the phenol and 4-cp mixture as the substrate. The effective toxicity of phenolic compounds to cells was highly dependent on their degradation pathways [33]. It is likely using the same degradation pathway, cells could use the same enzyme systems and eliminate the competition of different pathways to enhance the degradation efficiency [4]. Additionally catechol could inhibit the transformation of 4-cp and the meta-cleavage products of chlorocatechols were thought to be lethal or unable to support cell growth [34]. These findings could provide useful information for further investigating the phenols degradation. 4. Conclusions Metabolic profiling analysis was used for the first time to investigate the degradation of phenol and 4-cp by Pseudomonas sp. cbp1-3. Samples from different substrates (succinate, phenol, 4cp, and the mixture of phenol and 4-cp) were clearly separated by performing PCA on the detected intracellular metabolites in the score plot. Furthermore, it was found that phenols inhibited cell growth by reducing its primary metabolism while phenols enhanced the degradation of 4-cp in their mixed medium through accumulating amino acids, polyamines, and saturated fatty acids which were thought as the common tolerance mechanisms for cells. Besides, the accumulation of Cl− transduction carrier-MAGs and concentration changes of metabolites participating in phenols biodegradation aided in a deeper understanding of the degradation of phenols. The observed variations of intracellular metabolites led to a better understanding of the co-degradation of phenol and 4-cp and gave insights into the enhancement effect of phenol on 4chlorophenol at the intracellular molecular level. According to our results, primary metabolism, DO level, and the balance of reducing power should be considered for further enhancing the degradation of phenolic compounds. Additionally, the regulation of key enzymes associated in relative degradation pathways can be also modulated to enhance the degradation. By comparing metabolite changes of Pseudomonas sp. cbp1-3 in single substrate (phenol and 4-cp) and dual substrate (mixtures of phenol and 4-cp), results revealed that metabolomics is an effective tool to investigate the enhancement of phenol by 4-cp in their co-degradation. Although metabolomics studies have provided valuable information, it needs to be used in conjunction with
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